Scheduling tasks based on branch and bound algorithm in cloud computing environment

Abstract

Cloud computing is an ideal way for large-scale distributed computing and parallel processing. Cloud computing supports a vast number of services which covers a large number of consumer services like the cloud backup of the images, videos in the smartphone, etc. The performance and efficiency of services provided by cloud computing are dependent on the execution time of user tasks presented to the cloud system. Efficient scheduling of user tasks plays a significant role in managing the physical and virtual resources with a better performance in cloud services. Task Scheduling is one of the main types of scheduling performed in a cloud environment that aim to minimize the makespan for the task processing. Makespan means the total time taken by the virtual machines to complete the tasks allocated to them. In heterogeneous system scheduling the different size tasks of different significance is a complex problem that has been tried to resolve with various approaches e.g. FCFS, SJF, Min-Min, Max-Min, etc. In this work, the Branch and Bound (B&B) algorithm has been implemented and tested for assigning these heterogeneous tasks to virtual machines to reduce the makespan. It has configured the environment in the CloudSim simulator and obtained the results mainly about makespan. Results are compared with other general scheduling algorithms i.e. FCFS, MIN-MIN, MAX-MIN, and SJF.